Spare part management is essential to many organizations, since excess inventory leads to high holding costs and stock outs can greatly impact operations performance, but it is a major problem in the testing work shop in Robert Bosch China Diesel (RBCD) Wuxi. The workshop is used to test the functionality of the injectors, such as those statistics for pressure, electro conductivity, etc. After implementing the automated tower storage in the work shop, the workshop supervisor applied monthly order policy to purchase spare parts, which means at the end of each month, he/she will check the consumption of last month’s spare parts and make orders according to that data. However, in order to control the inventory of spare parts and achieve minimum total inventory cost of those parts, the (Q, r) model was suggested to make the monthly order, realizing the goal of maximizing the net profit of injectors.

A virtual factory should represent most of the features and operations of the corresponding real factory. Some of the key features of the virtual factory include the ability to assess performance at multiple resolutions and generate analytics data similar to that possible in a real factory. One should be able to look at the overall factory performance and be able to drill down to a machine and analyze its performance. It will require a large amount of effort and expertise to build such a virtual factory. This paper describes an effort to build a multiple resolution model of a manufacturing cell. The model provides the ability to study the performance at the cell level or at the machine level. The benefits and limitations of the presented approach and future research directions are also described.

A tunnel boring machine (TBM) is the primary resource in a tunnel construction project and generally its advance rate is equal to the performance rate of the whole project. Regarding previous studies, the utilization factor of TBMs is approximately 50% most of the time. The process of repair and maintenance of various parts of the machine and the logistic equipment takes 50% of the time. This case study aims to simulate the whole process of TBM tunneling in Ahwas subway project and find out how different scenarios of repair and maintenance can affect the utilization factor of the TBM. The model is developed using discrete-event simulation (DES) method.

The operation of offshore drilling platforms requires a lot of logistics: supply of platforms by platform supply vessels (PSVs), backward transportation of waste in containers and transportation of oil by tankers to export ports. The severe weather conditions of the Arctic Ocean increase the number of possible disruptions that influence the logistic system. The operation of PSVs and tankers has multiple constraints and interactions. An agent-based simulation has been developed in AnyLogic to support the strategic planning of logistics by year 2042. The presentation discusses the use of the model to determine the required number of vessels and compare different options of crude oil outbound logistic network design.

Many complex real-world problems which are difficult to understand can be solved by discrete or continuous
simulation techniques, such as Discrete-Event-Simulation, Agent-Based-Simulation or System Dynamics.
In recently published literature, various multilevel and large-scale hybrid simulation examples have been
presented that combine different approaches in common environments.

Workers cross-trained with multiple tasks can improve the workforce flexibility for the plant to handle
variations in workload. Therefore, it is necessary to study the dynamic multi-skilled workforce planning
problem of production line with the application of cross-training method.

Recargo has been developing an agent-based model with the AnyLogic tool to help us simulate the charging patterns of electric vehicle drivers in California. Our goal is to better understand the potential value from delivering electricity grid services with these vehicles. Development has only been underway for a few weeks, but in that time we’ve been able to use AnyLogic’s accessible interface and Java coding tools to quickly build and test a proof-of-concept model with which we can explore the potential for a more sophisticated and complex effort.

This paper presents an online simulation framework that can be used to support operational decisions within the context of Through-life Engineering Services. Acting as a closed-loop feedback control mechanism, the simulation model is physically coupled to the assets and will be triggered and automatically executed to assess a set of operational decisions related to maintenance scheduling, resource allocation, spare parts inventory etc. Experimental cases comparing the online simulation against the traditional approach will also be presented. The outcomes have demonstrated the prospects of the framework in enabling more effective/efficient operations of engineering services leading to high assets availability and reduced through-life costs.

This paper presents an agent-based model for simulating wind power systems on multiple time scales. The aim is to generate a flexible model that allows us to simulate the output of a wind farm. The model is developed using multiparadigm modelling, combining different approaches such as agent-based modelling, discrete events and dynamic systems.